With the development of the modern electronic technology, products, such as a camera and a scanner, are more widely applied in people's daily life and work. However, images captured by the product such as a camera and a scanner for an object (such as a document and a material object) may have certain distortions, such as perspective transformation distortion and tensile deformation distortion. In order to eliminate image distortion, obtaining accurately the boundary of the object becomes important.
Whatever boundary tracking method is used, it is impossible to obtain an accuracy rate of 100%. As a result, interaction with a user is often required during extracting a boundary of an object in an image, for example, a correct boundary point is input by the user by clicking a mouse. However, there is a lower accuracy when extracting the boundary of the object using the technology in which a boundary of an object is extracted based on the known boundary points.
In addition, some other conventional boundary extracting technologies adopt several control points to represent a whole curve, the user can adjust an ordinate of each control point, and a boundary curve is updated by locally fitting these control points. In order to adjust the whole curve, the user needs to manually adjust for many times, and the finally obtained curve is not smooth on the whole.